code: def test_art_handle_errors(self):
      with self.assertRaises(ValueError):
          # Invalid input data dimension
          artnet = algorithms.ART1(
              step=0.4, rho=0.1, n_clusters=3, verbose=False
          )
          artnet.predict(np.array([[[1]]]))
  
      with self.assertRaises(ValueError):
          # Non-binary input values
          artnet = algorithms.ART1(
              step=0.4, rho=0.1, n_clusters=3, verbose=False
          )
          artnet.predict(np.array([[0.5]]))
  
      with self.assertRaises(ValueError):
          # Invalid data size for second input
          artnet = algorithms.ART1(
              step=0.4, rho=0.1, n_clusters=3, verbose=False
          )
          artnet.predict(np.array([[1]]))
          artnet.predict(np.array([[1, 1]]))
  
file_path: neupy/tests/algorithms/competitive/test_art.py
imports: import numpy
  import pandas
  from sklearn import preprocessing
  from neupy import algorithms
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling the ARTTestCase obj's underlying member method code with example usage: obj.test_art_handle_errors() without return types